• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.221-235
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• 1998

Suppose that an observed process can be written as the additive model of the signal process and the noise process with unknown parameters. In practice the signal process is not directly observed. We consider the problem of estimating parameter from the observation process using the quasi-likelihood method.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.858-865
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• 2014

In the case of system like MES, various sensors collect the data in real time and save it as a big data to monitor the process. However, if there is big data mining in distributed computing system, whole processing process can be improved. In this paper, system to analyze the cause of operation deviation was built using the big data which has been collected from deasphalting process at the two different plants. By applying multivariate statistical analysis to the big data which has been collected through MES(Manufacturing Execution System), main cause of operation deviation was analyzed. We present the example of analyzing the operation deviation of deasphalting process using the big data which collected from MES by using multivariate statistics analysis method. As a result of regression analysis of the forward stepwise method, regression equation has been found which can explain 52% increase of performance compare to existing model. Through this suggested method, the existing petrochemical process can be replaced which is manual analysis method and has the risk of being subjective according to the tester. The new method can provide the objective analysis method based on numbers and statistic.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.482-487
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• 1988

A sequential-clustered integrator based on GEAR method is developed for the purpose of dynamic simulation of chemical processes. And a single simulator structure capable of employing various integration approaches is designed and its efficiency and flexiblity is evaluated. Sequential integration method is superior to simultaneous method for the process without recycle, but simultaneous method is very powerful for the coupled process with recycle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6590-6596
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• 2013

Carbon dioxide should be removed to increase the productivity of dimethyl ether(DME) from the DME manufacturing process. In this study, carbon dioxide can be removed using a physical absorbent through a solvent absorption method and membrane separation method. After performing the simulation for the carbon dioxide removal process, the energy consumption of the processes was compared. Methanol was used as a physical absorbent for the rectisol process, dimethyl ethers of polyethylene glycol for the Selexol process and N-methyl pyrrolidone for the Purisol process. By performing the simulation for each process, the energy consumption was compared. The Purisol process had the lowest energy consumption, followed in order by the Selexol process, Rectisol process and Membrane process. Therefore, the Purisol process was the most suitable method for the carbon dioxide process in the DME manufacturing process.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1685-1696
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• 1994

In this paper, a new forming process of the large-size forgings within the limit of forming loads is developed by introducing the incremental forging method and combined forming method. For the development of the forming process, various related processes are proposed and modelling experiments of plasticine and corresponding numerical simulation ate carried out. Thus, an optimal process considering the productivity and economical efficiency is recommended from the study of formability and forming loads, etc. The selected process is subjected to a modelling experiment of lead and 1/7 scale prototype experiment of the real material so as to verify the effectiveness of a selected process as well as to determine the design parameters. The developed process is then applied the forging product of dome shape. Dome-shaped forgings can be produced by the developed process within the limit loads and with the simple tools.

• Journal of the Korea Institute of Building Construction
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• v.2 no.1
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• pp.147-154
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• 2002

In the Past, The selection of individual method of construction was done by head of construction site or an experienced person very frequently. By doing this, The wrong selection of construction method without exact adjudication of construction site situation lead to increasing of cost and extension of construction term. Finally it will effect all over the construction process. Especially, In case of underground construction in the beginning, there are a lot of a variable factor and it also effect on the entire construction process and it need very careful process. The purpose of this study is to present the best suitable methodology for selection of construction method by considering potential risk of construction method and variables together with external condition for underground construction. The purpose of this study Is to select the most suitable construction method by analysing potential conditions(construction site situation and client request in designing ) To do this, We prepared arrangement rule to arrange the conditions for construction method. And thin make checklist of the analyzing construction method. Though above process, To expect the risk of individual construction method using above risk checklist and using Analytic Hierarchy process among Multiple-Criteria Decision making, the professional opinions is to be adapted. By doing this, it can lead and select the most suitable construction method considering the data which get from risk density test.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.604-609
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• 2001

In the sheet metal forming process, the drawbead is used to control the flow of material during the forming process. The drawbead provides proper restraining force to the material and prevents defects such as wrinkling or breakage. For these reasons, many studies for designing the effective drawbead have been conducted. For the analysis, the numerical method called the static-explicit finite element method was used. The finite element analysis code for this method has been developed and applied to the drawbead process problems. In result, convergence problem and computation time due to large non-linearity in the existing numerical analysis methods were no longer a critical problem. Futhermore, this approach could treat the contact friction problem easily by applying very small time intervals. It is expected that various results from the numerical analysis will give very useful information for the design of tools in sheet metal forming process.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.633-636
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• 2006

In order to determine new settings of key process variables optimally, a new rule induction method through a historical data is proposed without using an explicit functional model between process and quality variables. First, a partial least square is used to reduce the dimensionality of the process variables. Then new process settings that yield the best quality variable are identified by sequentially partitioning the reduced latent variable space using a patient rule induction method. The proposed method is illustrated with a case study obtained from steel-making processes. We also show, through simulation, that the proposed method gives more stable results than estimating an explicit function even when the form of the function is known in advance.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.344-347
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• 2007

For modeling the non-periodic and randomly scattered powder particles, the quasi-random multi-particle array is introduced. The multi-scale process simulation, which enables to formulate a regression model with a response surface method, is performed by employing a homogenization method. The size of ${Al_2}{O_3}$ particle, amplitude of cyclic compaction pressure, and friction coefficient are considered as optimal process parameters. The optimal conditions of process parameters providing the highest relative density are finally found by using the grid search method.